passive_invoices_v2

作者 atatavana · 下载 2 · 点赞 0 · 更新 2023-11-04

generated_from_trainer

passive_invoices_v2

This model is a fine-tuned version of microsoft/layoutlmv3-base on the sroie dataset. It achieves the following results on the evaluation set:

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 0.15 100 1.0334 0.3214 0.0118 0.0228 0.7802
No log 0.29 200 0.6691 0.4022 0.3336 0.3647 0.8314
No log 0.44 300 0.4943 0.5850 0.5537 0.5689 0.8905
No log 0.59 400 0.3823 0.7330 0.6461 0.6868 0.9336
0.9058 0.73 500 0.2996 0.7676 0.7119 0.7387 0.9447
0.9058 0.88 600 0.2370 0.7837 0.7617 0.7726 0.9553
0.9058 1.03 700 0.1981 0.7979 0.7799 0.7888 0.9594
0.9058 1.17 800 0.1755 0.8458 0.8127 0.8289 0.9671
0.9058 1.32 900 0.1558 0.8487 0.8262 0.8373 0.9702
0.256 1.47 1000 0.1470 0.8636 0.8219 0.8422 0.9709
0.256 1.62 1100 0.1317 0.8613 0.8442 0.8526 0.9734
0.256 1.76 1200 0.1282 0.8716 0.8413 0.8562 0.9751
0.256 1.91 1300 0.1249 0.8635 0.8479 0.8556 0.9739
0.256 2.06 1400 0.1172 0.8706 0.8645 0.8675 0.9763
0.153 2.2 1500 0.1171 0.8705 0.8612 0.8658 0.9758
0.153 2.35 1600 0.1120 0.8852 0.8660 0.8755 0.9775
0.153 2.5 1700 0.1057 0.8764 0.8645 0.8704 0.9772
0.153 2.64 1800 0.1044 0.8762 0.8621 0.8691 0.9777
0.153 2.79 1900 0.1023 0.8791 0.8708 0.8749 0.9784
0.1265 2.94 2000 0.1024 0.8956 0.8723 0.8838 0.9795
0.1265 3.08 2100 0.0999 0.8896 0.8702 0.8798 0.9793
0.1265 3.23 2200 0.0971 0.8883 0.8748 0.8815 0.9798
0.1265 3.38 2300 0.0948 0.8911 0.8783 0.8846 0.9802
0.1265 3.52 2400 0.0909 0.8918 0.8793 0.8855 0.9804
0.1044 3.67 2500 0.0902 0.8937 0.8748 0.8841 0.9805
0.1044 3.82 2600 0.0915 0.894 0.8793 0.8866 0.9808
0.1044 3.96 2700 0.0930 0.8949 0.8745 0.8846 0.9807
0.1044 4.11 2800 0.0913 0.8952 0.8809 0.8880 0.9810
0.1044 4.26 2900 0.0900 0.8938 0.8809 0.8873 0.9810
0.0872 4.41 3000 0.0901 0.8948 0.8791 0.8869 0.9808

Framework versions